Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Generative AI Fundamentals on Google Cloud
- Defining generative AI and its integration into business applications.
- Common use cases including text generation, chat, summarization, and search assistance.
- An overview of Google Cloud generative AI services and the role of Vertex AI.
- Key concepts such as models, prompts, context, and application workflows.
Working with Vertex AI Models
- Navigating the Google Cloud environment for generative AI projects.
- Accessing and testing foundation models within Vertex AI.
- Comparing model capabilities for various business scenarios.
- Conducting simple experiments and reviewing model responses.
Prompting and Output Quality
- Writing clear prompts that include instructions, context, and examples.
- Improving outputs for accuracy, format, tone, and consistency.
- Addressing common prompt issues such as vague responses and hallucinations.
- Practicing iterative prompt refinement for business tasks.
Building a Simple Generative AI Application
- Designing a basic application flow for chat, summarization, or content generation use cases.
- Connecting prompts, user input, and model responses into a streamlined workflow.
- Testing application behavior in a hands-on lab setting.
- Reviewing practical implementation considerations for real-world projects.
Grounding, Evaluation, and Responsible Use
- Understanding why grounding and enterprise context enhance response quality.
- Introduction to retrieval-augmented generation concepts for knowledge-based applications.
- Basic evaluation methods for prompts and outputs.
- Security, data privacy, access control, and responsible AI considerations on Google Cloud.
From Prototype to Next Steps
- Transitioning from a proof of concept to a robust business solution.
- Monitoring usage, reviewing results, and refining prompts over time.
- Identifying realistic next steps for adoption within a team or organization.
- Course wrap-up and recommendations for further learning.
Requirements
- A fundamental understanding of cloud computing concepts and standard business application workflows.
- Prior experience using the Google Cloud Console or a comparable cloud platform.
- Basic proficiency in programming or scripting.
Audience
- Developers and technical professionals involved in creating AI-enabled applications.
- Cloud engineers and solution architects working on Google Cloud initiatives.
- Product teams and technical managers exploring practical use cases for generative AI.
7 Hours
Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
A great repository of resources for future use, instructor's style (full of good sense of humor, great level of detail)
